Hi everyone,
I want to deploy a Hugging Face Transformer model on OpenShift. What are the recommended steps to containerize the model and deploy it as a service?
I’m exploring ways to integrate Hugging Face Transformers into a Red Hat OpenShift environment and would love to get some advice from the community on the best practices and steps involved. Here’s what I’m hoping to achieve:
Are there specific configurations or settings in OpenShift that I need to be aware of for running large models efficiently? For example, should I adjust resource limits or use specific storage solutions?
What are the best practices for scaling Hugging Face model deployments in OpenShift? How can I ensure that the deployment scales effectively with the load?
What security measures should I take when deploying models, especially considering data privacy and model integrity?
How can I set up monitoring and logging for Hugging Face models running on OpenShift? Are there any tools or integrations that work particularly well for this?
If anyone has experience or has worked on similar integrations, could you please share any examples, resources, or documentation that might be helpful?
I’ve seen that OpenShift has robust support for containerized applications, but I’m keen to understand the nuances involved with machine learning models, especially those from Hugging Face. Any tips, insights, or shared experiences would be greatly appreciated!
Thanks in advance for your help!
Best, tammygombez